Meteorological Observatory Lindenberg – Richard Assmann Observatory
The
GCOS Reference
Upper Air Network
Meteorological Observatory Lindenberg – Richard Assmann Observatory
What is GRUAN?
GCOS Reference Upper Air Network Network for ground-based reference observations for climate in
the free atmosphere in the frame of GCOS
Initially 15 stations, envisaged to be a network of 30-40 sites across the globe
See www.gruan.org for more detail
Meteorological Observatory Lindenberg – Richard Assmann Observatory
Provide long-term high-quality upper-air climate records
Constrain and calibrate data from more spatially-comprehensive global observing systems (including satellites and current radiosonde networks)
Fully characterize the properties of the atmospheric column
GRUAN tasks
Meteorological Observatory Lindenberg – Richard Assmann Observatory
GRUAN goals
Maintain observations over several decades for accurately estimating climate variability and change
Focus on characterizing observational biases, including complete estimates of measurement uncertainty
Ensure traceability of measurements by comprehensive metadata collection and documentation
Ensure long-term stability by managing instrumental changes
Tie measurements to SI units or internationally accepted standards
Measure a large suite of co-related climate variables with deliberate measurement redundancy
Priority 1: Water vapor, temperature, (pressure and wind)
Priority 2: Ozone, clouds, …
Meteorological Observatory Lindenberg – Richard Assmann Observatory
GRUAN structure
GCOS/WCRP AOPC Working Group on Atmospheric Reference Observations (WG-ARO)
GRUAN Lead Centre at the Lindenberg Meteorological Observatory (DWD)
GRUAN sites world wide (currently 15 to be expanded to 30-40)
GRUAN task teams for Radiosondes GNSS-Precipitable Water Measurement schedules and associated site requirements Ancillary measurements Site representation
GRUAN Analysis Team for Network Design and Operations Research (GATNDOR)
See www.gruan.org for more detail
Meteorological Observatory Lindenberg – Richard Assmann Observatory
Focus on reference observations
A GRUAN reference observation:
Is traceable to an SI unit or an accepted standard
Provides a comprehensive uncertainty analysis
Is documented in accessible literature
Is validated (e.g. by intercomparison or redundant observations)
Includes complete meta data description
Meteorological Observatory Lindenberg – Richard Assmann Observatory
Establishing reference quality
Meteorological Observatory Lindenberg – Richard Assmann Observatory
Establishing Uncertainty
• Error is replaced by uncertainty
Important to distinguish contributions from systematic error and random error
• A measurement is described by a range of values
generally expressed by m ± u
m is corrected for systematic errors
u is random uncertainty
Literature:
Guide to the expression of uncertainty in measurement (GUM, 1980)
Guide to Meteorological Instruments and Methods of Observation, WMO 2006, (CIMO Guide)
Reference Quality Upper-Air Measurements: Guidance for developing GRUAN data products, Immler et al. (2010), Atmos. Meas. Techn.
Meteorological Observatory Lindenberg – Richard Assmann Observatory
Uncertainty, Redundancy and Consistency
GRUAN stations should provide redundant measurements
Redundant measurements should be consistent:
No meaningful consistency analysis possible without uncertainties
if m2 has no uncertainties use u
2 = 0 (“agreement within errorbars”)
22
2121 uukmm
Meteorological Observatory Lindenberg – Richard Assmann Observatory
Uncertainty, Redundancy and Consistency
Understand the uncertainties:
Analyze sources: Identify, which sources of measurement uncertainty are systematic (calibration, radiation errors, …), and which are random (noise, production variability …). Document this.
Synthesize best uncertainty estimate:
Uncertainties for every data point, i.e. vertically resolved
Use redundant observations:
to manage change
to maintain homogeneity of observations across network
to continuously identify deficiencies
Meteorological Observatory Lindenberg – Richard Assmann Observatory
Co-location / co-incidence:
Determine the variability () of a variable (m) in time and space from measurement or model
Two observations on different platforms are consistent if
This test is only meaningful, i.e. observations are co-located or co-incident if:
Consistency in a finite atmospheric region
22
21
221 uukmm
22
21 uu
Meteorological Observatory Lindenberg – Richard Assmann Observatory
Uncertainty example: Daytime temperature Vaisala RS92
Sources of measurement uncertainty (in order of importance):
Sensor orientation
Radiative heating of sensor
Unknown radiation field
Ventilation
Ground check
Calibration
Time lag
Meteorological Observatory Lindenberg – Richard Assmann Observatory
Uncertainty example: Comparison Vaisala RS92 with Multithermistor
Minor systematic difference at night
Significant systematic difference during the day
But observations are consistent with the understanding of the uncertainties in the Vaisala temperature measurements
Lack of uncertainties in Multithermistor measurements precludes further conclusions
Meteorological Observatory Lindenberg – Richard Assmann Observatory
Principles of GRUAN data management
Archiving of raw data is mandatory
All relevant meta-data is collected and stored in a meta-data base (at the lead centre)
For each measuring system just one data processing center
Version control of data products. Algorithms need to be traceable and well documented.
Data levels for archiving: level 0: raw data level 1: raw data in unified data format (pref. NetCDF) level 2: processed data product → dissemination (NCDC)
Meteorological Observatory Lindenberg – Richard Assmann Observatory
Distributed data processingGRUAN data flow
GRUAN sites
Data processing center
GRUAN Meta-data-base(at GRUAN lead center) raw
data archive
DATA dissemination (at NCDC)
datadocumentation
Meteorological Observatory Lindenberg – Richard Assmann Observatory
Summary
GRUAN is a new approach to long term observations of upper air essential climate variables
Focus on priority 1 variables to start: Water vapor and temperature
Focus on reference observation: quantified uncertainties traceable well documented
Understand the uncertainties: analyze sources synthesize best estimate verify in redundant observations
GRUAN requires a new data processing and data storage approach